GPT Memory is a package that stores historical memory of your LLM conversations and uses these memories to improve subsequent interactions. The system automatically classifies the memories and generates abstracts to behave like how human making conversations.
- Historical Memory Storage: Stores and manages historical chat data.
- Automatic Classification: Automatically classifies chat memories for better organization.
- Abstract Generation: Generates abstracts of past conversations to enhance GPT's context handling.
- Mood detection: Check user emotional status and store in history chat data.
- Context generation: Generates context for current message based on historical conversation.
To install GPT Memory, use pip:
pip install gpt_memoryTo start using GPT Memory, import the Memory class and process a user message:
from gpt_memory import Memory
m = Memory()
response = m.process_message('user_message')Here’s a simple example of how to use the Memory class:
from gpt_memory import Memory
# Initialize the memory system
memory_system = Memory()
# Process a user message
response = memory_system.process_message('Hello, how are you?')
# Print the status and response
print(f"Response: {response}")If you would like to contribute to GPT Memory, please follow these steps:
- Fork the repository.
- Create a new branch for your feature or bugfix.
- Implement your changes.
- Submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for details.
For any questions or inquiries, please contact sun@raaslabs.com.